This paper explores event data as an abstract statistical object. It briefly traces the historical development of event data, with particular attention to how nominal events have come to be used primarily in interval-level studies. A formal definition of event data and its stochastic error structure is presented. From this definition, some concrete suggestions are made for statistically compensating for misclassification and censoring errors in frequency-based studies. The paper argues for returning to the analysis of events as discrete structures. This type of analysis was not possible when event data were initially developed, but electronic information processing capabilities have improved dramatically in recent years and many new techniques for generating and analyzing event data may soon be practical.
All Science Journal Classification (ASJC) codes
- Political Science and International Relations